Qi Jinqing   

Associate Professor
Supervisor of Master's Candidates

MORE> Recommended MA Supervisor Institutional Repository Personal Page
Language:English

Paper Publications

Title of Paper:Restricted Boltzmann Machine for Saliency Detection

Hits:

Date of Publication:2015-09-22

Included Journals:EI、CPCI-S、Scopus

Page Number:19-24

Key Words:Saliency; Restricted Boltzmann Machine; Optimization

Abstract:Saliency detection is the task of locating informative regions and objects in an image, which is a challenging task in computer vision. In this paper, we introduce an effective generative model using the Restricted Boltzmann Machine (RBM) for salient object detection. First, RBM is adopted to model the global shape of input images based on regional features. Second, an effective optimization method is used to refine the initial shape map with local relations and detailed information. Experimental results on benchmark datasets demonstrate that the proposed RBM model for saliency detection works more effectively than some existing state-of-the-art algorithms.

Address: No.2 Linggong Road, Ganjingzi District, Dalian City, Liaoning Province, P.R.C., 116024
Click:    MOBILE Version DALIAN UNIVERSITY OF TECHNOLOGY Login

Open time:..

The Last Update Time: ..